Development Of Quantitative FT- IR Methods For Analyzing The Cure Kinetics Of Epoxy Resins

Epoxy thermosets are important engineering materials with applications in coating, adhesives, packaging and as structural components in a variety of advanced engineering products. The ultimate performance of polymer critically depends upon the details of the cure chemistry used to produce the thermoset. In order to better understand and monitor the cure chemistry, quantitative analysis of the FT-IR response has been developed for describing the epoxy-amine curing reaction as well as monitoring the hydrogen bonding that occurs in these systems The FT-IR analysis includes (i) quantitative deconvolution of complex peaks into individual spectral contributions, (ii) peak identification via DFT analysis and (iii) appropriate baseline correction. These FT-IR analysis methods were utilized to resolve spectral complexity in epoxy-amine thermoset resin systems. Using the quantitative FT-IR tools described above, the hydrogen bonding of amine and hydroxyl groups was determined for (i) the self association and inter-association of N-methylaniline (NmA) and isopropanol and (ii) the reaction with a series of hydrogen bonding acceptors, including toluene, triethylamine, epoxy butane and dipropylether that represent ð-bond, electron pair on amine, epoxide and ether groups. Simple mass-action equilibrium models of the amine and hydroxyl group hydrogen bonding were developed, where both the extinction coefficient and equilibrium constants were determined from the data. However, this simple analysis was only valid for dilute concentrations, where an unexpected maximum in the free hydrogen as measured by FT-IR vs. total amount of NmA or isopropanol was observed. It was postulated that a phase transition occurs at high NmA or isopropanol concentrations. The epoxy-amine reaction kinetics was studied using quantitative FT-IR. First, the reaction kinetics of a monoepoxide with a monoamine was studied, where reaction kinetics was followed by (i) HPLC analysis and (ii) then compared with FT-IR analysis. Subsequently, quantitative FT-IR was applied to the thermoset system of a digylcidyl ether of bisphenol-A epoxy cured with aniline, where multiple absorbance profiles for the different vibrational peaks enabled self-consistent determination of the various reacting species. This analysis demonstrates the power of quantitative FT-IR analysis to follow detailed reaction kinetics in thermoset systems. The effect of temperature on the FT-IR spectra was measured for the fully cured Epon825-aniline system, where the hydrogen bonding peaks exhibited significant changes in temperature dependence of the absorbance near the Tg of 95C. Finally relaxation of fully cured polymer was examined by observing the absorbance evolution following a temperature jump. In summary, quantitative FT-IR analysis provides valuable information on the chemical kinetics in curing thermoset systems as well as changes in the structure of the resulting glassy thermoset with temperature and sub-Tg thermal annealing

Development of Scalable Simulator for Spiking Neural Network

A neural network simulator for Spiking Neural Network (SNN) is a useful research tool to model brain functions with a computer. With this tool, different parameters can be explored easily compared to using a real brain. For several decades, researchers have developed many software packages and simulators to accelerate research in computational neuroscience. However, despite their advantages, different neural simulators possess different limitations, such as flexibility of choosing different neuron models and scalability of simulators for large numbers of neurons. This paper demonstrates an efficient and scalable spiking neural simulator that is based on growth transform neurons and runs on a single machine. The growth transform neuron model’s update is based on matrix-vector multiplication, which is optimized using external libraries named BLAS and sparseBLAS. Using sparseBLAS, the scalability of the simulator was optimized with sparse representation of matrix. The optimized tool can simulate up to 1 million neurons and is flexible with neuron model changes behind the simulator. Furthermore, with a simple graphical user interface, a researcher can easily design a variety of network topology with different parameters. He/she can visualize a coupling matrix, simulate a designed network and study the spike train with spike raster plot. This simulator will be made open source so that researchers can benefit from this for large-scale simulations

The Progress of Paperless Trade in Asia and the Pacific: Enabling International Supply Chain Integration

This paper discusses on how to facilitate paperless trade for international supply chain integration in the Asia and Pacific region. The paper defines paperless trade and describes how paperless trade can improve efficiency of international supply chain, including its economic benefits. Based on the review of paperless trade initiatives and assessment of paperless trade readiness of countries in the Asia and Pacific region, the paper identifies five critical challenges in facilitating cross-border paperless trade: use of common international standards, harmonization of different legal frameworks, capacity gaps among the parties, cooperation between the public and private sectors, and lack of coordination mechanisms for cross-border data exchanges. For each challenge, the paper describes its nature and possible measures for alleviating it. In its annexes, the paper also provides implementation cases of cross-border paperless trade in the Asia and Pacific region, namely Pan Asian e-Commerce Alliance (PAA) and electronic Certificate of Origin between the Republic of Korea and Taipei,China